Tae-Chon Ahn - RankMe

35 papers B 1C 2Misc 3Journal 13Unranked 15

Year	Rank	Type	Title / Venue / Authors
2020	J	`jnl`	Lazy Learning for Nonparametric Locally Weighted Regression. Int. J. Fuzzy Log. Intell. Syst. Seok-Beom Roh, Yong-Soo Kim, Tae-Chon Ahn
2019	J	`jnl`	Prototypes Reduction and Feature Selection based on Fuzzy Boundary Area for Nearest Neighbor Classifiers. Int. J. Fuzzy Syst. Tae-Chon Ahn, Seok-Beom Roh, Yong-Soo Kim, Jihong Wang
2014	J	`jnl`	A design of granular fuzzy classifier. Expert Syst. Appl. Seok-Beom Roh, Witold Pedrycz, Tae-Chon Ahn
2014	—	`ch.`	Design of Radial Basis Function Classifier Based on Polynomial Neural Networks. Soft Computing in Artificial Intelligence Tae-Chon Ahn, Seok-Beom Roh, Zi Long Yin, Yong-Soo Kim
2012	J	`jnl`	Fuzzy linear regression based on Polynomial Neural Networks. Expert Syst. Appl. Seok-Beom Roh, Tae-Chon Ahn, Witold Pedrycz
2011	J	`jnl`	Fuzzy Learning Vector Quantization based on Fuzzy k-Nearest Neighbor Prototypes. Int. J. Fuzzy Log. Intell. Syst. Seok-Beom Roh, Ji-Won Jeong, Tae-Chon Ahn
2010	J	`jnl`	The Refinement of Models With the Aid of the Fuzzy k -Nearest Neighbors Approach. IEEE Trans. Instrum. Meas. Seok-Beom Roh, Tae-Chon Ahn, Witold Pedrycz
2010	J	`jnl`	The design methodology of radial basis function neural networks based on fuzzy K-nearest neighbors approach. Fuzzy Sets Syst. Seok-Beom Roh, Tae-Chon Ahn, Witold Pedrycz
2007	—	`conf`	Design of Adaptive Fuzzy-PI Control with the Aid of Rough Set Theory and Its Application to a HVDC System. ICIC (1) Zhong-Xian Wang, Tae-Chon Ahn
2007	—	`conf`	Fuzzy Combined Polynomial Neural Networks. KES (3) Seok-Beom Roh, Tae-Chon Ahn
2007	—	`conf`	GA-Driven Fuzzy Set-Based Polynomial Neural Networks with Information Granules for Multi-variable Software Process. ISNN (2) Seok-Beom Roh, Sung-Kwun Oh, Tae-Chon Ahn
2007	J	`jnl`	IG-based genetically optimized fuzzy polynomial neural networks with fuzzy set-based polynomial neurons. Neurocomputing Sung-Kwun Oh, Seok-Beom Roh, Witold Pedrycz, Tae-Chon Ahn
2006	—	`conf`	A New Design Methodology of Fuzzy Set-Based Polynomial Neural Networks with Symbolic Gene Type Genetic Algorithms. ISNN (1) Seok-Beom Roh, Sung-Kwun Oh, Tae-Chon Ahn
2006	—	`conf`	A Novel Self-Organizing Fuzzy Polynomial Neural Networks with Evolutionary FPNs: Design and Analysis. ISNN (1) Ho-Sung Park, Sung-Kwun Oh, Tae-Chon Ahn
2006	—	`conf`	An Advanced Design Methodology of Fuzzy Set-Based Polynomial Neural Networks with the Aid of Symbolic Gene Type Genetic Algorithms and Information Granulation. ICONIP (3) Seok-Beom Roh, Hyung-Soo Hwang, Tae-Chon Ahn
2006	J	`jnl`	Data Pattern Estimation with Movement of the Center of Gravity. Int. J. Fuzzy Log. Intell. Syst. Tae-Chon Ahn, Kyung-Won Jang, Dong-Du Shin, Hak-Soo Kang, Yang-Woong Yoon
2006	—	`conf`	Design Methodology of Optimized IG_gHSOFPNN and Its Application to pH Neutralization Process. ICONIP (3) Ho-Sung Park, Kyung-Won Jang, Sung-Kwun Oh, Tae-Chon Ahn
2006	C	`conf`	Evolutionary Design of gdSOFPNN for Modeling and Prediction of NOx Emission Process. IDEAL Tae-Chon Ahn, Ho-Sung Park
2006	—	`conf`	Genetically Optimized Fuzzy Set-Based Polynomial Neural Networks Based on Information Granules with Aids of Symbolic Genetic Algorithms. KES (3) Tae-Chon Ahn, Kyung-Won Jang, Seok-Beom Roh
2006	—	`conf`	Improvement of HSOFPNN Using Evolutionary Algorithm. Australian Conference on Artificial Intelligence Ho-Sung Park, Sung-Kwun Oh, Tae-Chon Ahn
2006	J	`jnl`	Intuitionistic Fuzzy Subgroups and Level Subgroups. Int. J. Fuzzy Log. Intell. Syst. Tae-Chon Ahn, Kul Hur, Kyung-Won Jang
2006	J	`jnl`	Optimal Fuzzy Models with the Aid of SAHN-based Algorithm. Int. J. Fuzzy Log. Intell. Syst. Jong-Seok Lee, Kyung-Won Jang, Tae-Chon Ahn
2006	C	`conf`	Optimization of Self-organizing Fuzzy Polynomial Neural Networks with the Aid of Granular Computing and Evolutionary Algorithm. IEA/AIE Ho-Sung Park, Sung-Kwun Oh, Tae-Chon Ahn
2006	—	`conf`	The Analysis and Design of IG_gHSOFPNN by Evolutionary Optimization. FSKD Ho-Sung Park, Tae-Chon Ahn
2006	—	`conf`	The Design of Self-tuning Strategy of Genetically Optimized Fuzzy-PI Controller for HVDC System. KES (1) Zhong-Xian Wang, Jueng-je Yang, Tae-Chon Ahn
2005	—	`conf`	Design of Information Granules-Based Fuzzy Systems Using Clustering Algorithm and Genetic Optimization. Australian Conference on Artificial Intelligence Sung-Kwun Oh, Keon-Jun Park, Witold Pedrycz, Tae-Chon Ahn
2005	Misc	`conf`	Genetically Optimized Hybrid Fuzzy Neural Networks Based on Simplified Fuzzy Inference Rules and Polynomial Neurons. International Conference on Computational Science (1) Sung-Kwun Oh, Byoung-Jun Park, Witold Pedrycz, Tae-Chon Ahn
2005	Misc	`conf`	Identification of Fuzzy Systems with the Aid of Genetic Fuzzy Granulation. IWANN Sung-Kwun Oh, Keon-Jun Park, Yong-Soo Kim, Tae-Chon Ahn
2005	—	`conf`	Parameter Estimation of Fuzzy Controller Using Genetic Optimization and Neurofuzzy Networks. ISNN (3) Sung-Kwun Oh, Seok-Beom Roh, Tae-Chon Ahn
2004	Misc	`conf`	Information Granulation-Based Multi-layer Hybrid Fuzzy Neural Networks: Analysis and Design. International Conference on Computational Science Byoung-Jun Park, Sung-Kwun Oh, Witold Pedrycz, Tae-Chon Ahn
2004	J	`jnl`	Parameter estimation of fuzzy controller and its application to inverted pendulum. Eng. Appl. Artif. Intell. Sung-Kwun Oh, Witold Pedrycz, Seok-Beom Roh, Tae-Chon Ahn
2003	—	`conf`	Genetically Optimized Rule-Based Fuzzy Polynomial Neural Networks: Synthesis of Computational Intelligence Technologies. RSFDGrC Sung-Kwun Oh, James F. Peters, Witold Pedrycz, Tae-Chon Ahn
2002	—	`conf`	Obstacle Classification by a Line-Crawling Robot: A Rough Neurocomputing Approach. Rough Sets and Current Trends in Computing James F. Peters, Tae-Chon Ahn, Maciej Borkowski
2002	J	`jnl`	Self-organizing neural networks with fuzzy polynomial neurons. Appl. Soft Comput. Sung-Kwun Oh, Witold Pedrycz, Tae-Chon Ahn
2002	B	`conf`	Software Quality Knowledge Discovery: A Rough Set Approach. COMPSAC Sheela Ramanna, James F. Peters, Tae-Chon Ahn

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.